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BACKGROUND Medication adherence is crucial to the efficacy of antitumor drugs. The wechat applet, also known as the Mini Program, similar to app but has great advantages. The development and use of wechat applet provide follow-up convenience for cancer patients. OBJECTIVE This study aimed to assess the usability and utility of a newly developed medication adherence wechat applet—DolphinCare—among cancer patients in Shanghai. METHODS A qualitative methodology was utilized to obtain an in-depth understanding of users’ experiences when using DolphinCare from the usability and utility aspects. The development phase consisted of two parts: alpha and beta testing. The medication adherence of patients was evaluated using the eight-item Morisky Medication Adherence Scale (MMAS-8). RESULTS We included participants who had an electronic health literacy scale (eHEALS) of ≥50%, and a total of 20 participants were interviewed consecutively. We used the motivation, ability and trigger categories of the Fogg behaviour model to explore why patients adopted and adhered to our applet using data from the qualitative interviews and usage data. There were usabilities and utilities that could improve the patients’ medication adherence and the management of adverse drug reactions (ADRs). CONCLUSIONS This study provides beginning evidence of the usability and utility of this type of applet in cancer patients.

In the past decade, single-cell technologies have revealed the heterogeneity of the tumor-immune microenvironment at the genomic, transcriptomic, and proteomic levels and have furthered our understanding of the mechanisms of tumor development. Single-cell technologies have also been used to identify potential biomarkers. However, spatial information about the tumor-immune microenvironment such as cell locations and cell–cell interactomes is lost in these approaches. Recently, spatial multi-omics technologies have been used to study transcriptomes, proteomes, and metabolomes of tumor-immune microenvironments in several types of cancer, and the data obtained from these methods has been combined with immunohistochemistry and multiparameter analysis to yield markers of cancer progression. Here, we review numerous cutting-edge spatial ‘omics techniques, their application to study of the tumor-immune microenvironment, and remaining technical challenges.

In this paper, the flow field around NACA0015 hydrofoil is calculated under the condition of two-phase cavitating flow to provide a theoretical guidance for reducing the cavitation noise. A modified turbulence model coupled with the Zwart cavitation model is used to calculate the flow field. According to the computed sound source data, the dipole sound pressure distribution diagrams for the extremely short time and the complete time around the hydrofoil under different working conditions are obtained. The sound pressure distribution and the sound pressure amplitude are analyzed in detail. In addition, the field points around the hydrofoil are selected to generate the corresponding frequency response function curves, which are analyzed from the aspects of the trend, the variation and the extreme value. The results show that the dipole characteristics are gradually diminished and finally disappear with the increase of the frequency. At the frequency of the vapor volume fraction fluctuation, the noise level at the field point will have an extreme value.

Forest biomass is an important index in forest development planning and forest resource monitoring. In order to provide a more efficient and low-biased method for estimating individual tree biomass, we introduced artificial neural network here. We used the data of aboveground biomass of 101森林生物量是林业生产经营和森林资源监测的重要指标,为探索高效低偏的单木生物量估测方法,引入人工神经网络。本研究采用黑龙江省东折棱河林场的101株长白落叶松地上生物量数据,基于不同变量(胸径、树高、冠幅)组合建立了4个聚合模型体系(AMS),采用加权回归消除模型的异方差。然后,基于最优的变量组合建立人工神经网络(ANN)生物量模型,并采用留一交叉验证法对模型进行检验,比较两种生物量估测方法的精度。结果表明: 仅基于胸径一个变量的生物量模型已经能较准确地估测生物量,引入树高和冠幅因子能进一步提高模型精度,最优模型体系为AMS4。通过两种方法建立的生物量模型都能较准确地进行估测,各组分生物量的决定系数(

To explore how the immune system controls clearance of SARS-CoV-2, we used a single-cell, mass cytometry-based proteomics platform to profile the immune systems of 21 patients who had recovered from SARS-CoV-2 infection without need for admission to an intensive care unit or for mechanical ventilation. We focused on receptors involved in interactions between immune cells and virus-infected cells. We found that the diversity of receptor repertoires on natural killer (NK) cells was negatively correlated with the viral clearance rate. In addition, NK subsets expressing the receptor DNAM1 were increased in patients who more rapidly recovered from infection. Ex vivo functional studies revealed that NK subpopulations with high DNAM1 expression had cytolytic activities in response to target cell stimulation. We also found that SARS-CoV-2 infection induced the expression of CD155 and nectin-4, ligands of DNAM1 and its paired coinhibitory receptor TIGIT, which counterbalanced the cytolytic activities of NK cells. Collectively, our results link the cytolytic immune responses of NK cells to the clearance of SARS-CoV-2 and show that the DNAM1 pathway modulates host-pathogen interactions during SARS-CoV-2 infection.

This study applies statistical process control and machine learning techniques to diagnose wind turbine faults and predict maintenance needs by analyzing 2.8 million sensor data collected from 31 wind turbines from 2015 to 2017 in Taiwan. Unlike previous studies that only relied on historical wind turbine data, this study analyzed the sensor data with practitioners' insight by incorporating maintenance check list items into the data mining processes. We used Pareto analyses, scatter plots, and the cause and effect diagram to cluster and classify the failure types of wind turbines. In addition, control charts were used to establish a monitoring mechanism to track whether operation data are deviated from the controls (i.e., standard deviations) as a mean to detect wind turbine abnormalities. While statistical process control was applied to fault diagnosis, machine learning algorithms were used to predict maintenance needs of wind turbines. First, the density-based spatial clustering of applications with noise algorithm was used to classify abnormal-state wind turbine data from normal-state data. Then, random forest and decision tree algorithms were employed to construct the predictive models for wind turbine anomalies and tested with K-fold cross-validation. The results indicate a high level of accuracy: 92.68% for the decision tree model, and 91.98% for the random forest model. The study demonstrates that, by data mining and modeling, the failures of wind turbines can be detected, and the maintenance needs of parts can be predicted. Model results may provide technicians early warnings, improve equipment efficient, and decrease system downtime of wind turbine operation.

Objective— Vascular smooth muscle cell (VSMC) transformation to an osteochondrogenic phenotype is an initial step toward arterial calcification, which is highly correlated with cardiovascular disease–related morbidity and mortality. TLR2 (Toll-like receptor 2) plays a pathogenic role in the development of vascular diseases, but its regulation in calcification of arteries and VSMCs remains unclear. We postulate that TLR2-mediated inflammation participates in mediating atherosclerotic arterial calcification and VSMC calcification. Approach and Results— We found that ApoE −/− Tlr2 −/− genotype in mice suppressed high-fat diet–induced atherosclerotic plaques formation during initiation but progressively lost its preventative capacity, compared with ApoE −/− mice. However, TLR2 deficiency prohibited high-fat diet–induced advanced atherosclerotic calcification, chondrogenic metaplasia, and OPG (osteoprotegerin) downregulation in the calcified lesions. Incubation of VSMCs in a calcifying medium revealed that TLR2 agonists significantly increased VSMC calcification and chondrogenic differentiation. Furthermore, TLR2 deficiency suppressed TLR2 agonist–mediated VSMC chondrogenic differentiation and consequent calcification, which were triggered via the concerted actions of IL (interleukin)-6–mediated RANKL (receptor activator of nuclear factor κB ligand) induction and OPG suppression. Inhibition experiments with pharmacological inhibitors demonstrated that IL-6–mediated RANKL induction is signaled by p38 and ERK1/2 (extracellular signal-regulated kinase 1/2) pathways, whereas the OPG is suppressed via NF-κB (nuclear factor κB) dependent signaling mediated by ERK1/2. Conclusions— We concluded that on ligand binding, TLR2 activates p38 and ERK1/2 signaling to selectively modulate the upregulation of IL-6–mediated RANKL and downregulation of OPG. These signaling pathways act in concert to induce chondrogenic transdifferentiation of VSMCs, which in turn leads to vascular calcification during the pathogenesis of atherosclerosis.

Rechargeable batteries are critical components for the performance of portable electronics and electric vehicles. The long-term health performance of rechargeable batteries is characterized by state of health, which can be quantified by end of performance (EOP) and remaining useful performance. Focusing on EOP prediction, this article first proposes an accelerated testing version of the trend-renewal process model to address this decision problem. The proposed model is also applied to a real case study. Finally, a NASA dataset is used to address the prediction performance of the proposed model. Comparing with the existing prediction methods and time series models, our proposed procedure has better performance in the EOP prediction.

Atom migration, phase structure and magnetic properties in the Fe82Si2B11P4Cu1 amorphous alloy isothermally annealed at various heating rates are investigated. Annealing the samples at a high heating rate promotes the formation of Cu-rich regions and delays the phase separation process to high temperature, which is conductive to increase the volume fraction of the nanocrystalline phase and refine nanograins during the crystallization. When the alloy is isothermally annealed at 758 K for 180 s, the saturation magnetic flux density increases from 1.74 T to 1.79 T and the coercivity decreases from 7.8 A/m to 4.4 A/m with the heating rate increasing from 0.5 K/s to 20 K/s. Meanwhile, it confirms that the occupation of Si atoms in the lattice of bcc-Fe can be suppressed by the annealing with high heating rate. Increasing the heating rate is widely regarded as an effective method to improve soft magnetic properties of Fe-based nanocrystalline alloys. However, it is found that the content of the nonmagnetic atom enriched regions rises with the increase of heating rate, which can reduce the magnetic interaction in the nanocrystalline ribbons. Therefore, the exorbitant heating rate reaching 40 K/s will dramatically promote the aggregation of nonmagnetic atoms and deteriorate the soft magnetic properties.

In this work, an attempt has been made to reveal critical factors dominating the crystallization and soft magnetic properties of Fe81Si x B10P8−xCu1 (x = 0, 2, 4, 6 and 8) alloys. Both melt spun and annealed alloys are characterized by differential scanning calorimetry, X-ray diffractometry, Mössbauer spectroscopy, transmission electron microscopy, positron annihilation lifetime spectroscopy and magnetometry. The changes in magnetic interaction between Fe atoms and chemical homogeneity can well explain the variation of magnetic properties of Fe81Si x B10P8−xCu1 amorphous alloys. The density of nucleation sites in the amorphous precursors decreases in the substitution of P by Si. Meanwhile, the precipitated nanograins gradually coarsen, but the inhibiting effect of P on grain growth diminishes causing the increase of the crystallinity. Moreover, various site occupancies of Si are observed in the nanocrystallites and the Si occupancy in bcc Fe decreases the average magnetic moment of nanograins. Without sacrificing amorphous forming ability, we can obtain FeSiBPCu nanocrystalline alloy with excellent soft magnetic properties by optimizing the content of Si and P in the amorphous precursors.

Rice blast caused by Magnaporthe oryzae (M. oryzae) is a major threat to global rice production. In recent years, small interference RNAs (siRNAs) and host-induced gene silencing (HIGS) has been shown to be new strategies for the development of transgenic plants to control fungal diseases and proved a useful tool to study gene function in pathogens. We here tested whether in vitro feeding artificial siRNAs (asiRNAs) could compromise M. oryzae virulence and in vivo HIGS technique could improve rice blast resistance. Our data revealed that silencing of M. oryzae MoAP1 by feeding asiRNAs targeting MoAP1 (i.e., asiR1245, asiR1362, and asiR1115) resulted in inhibited fungal growth, abnormal spores, and decreased pathogenicity. Among the asiRNAs, asiR1115 was the most inhibitory toward the rice blast fungus. Conversely, the asiRNAs targeting three other genes (i.e., MoSSADH, MoACT, and MoSOM1) had no effect on fungal growth. Transgenic rice plants expressing RNA hairpins targeting MoAP1 exhibited improved resistance to 11 tested M. oryzae strains. Confocal microscopy also revealed profoundly restricted appressoria and mycelia in rice blast-infected transgenic rice plants. Our results demonstrate that in vitro asiRNA and in vivo HIGS were useful protection approaches that may be valuable to enhance rice blast resistance.

Systemic inflammation has emerged as a key pathophysiological process that induces multiple organ injuries and causes serious human diseases. Despite substantial evidence supporting the role of diacylglycerols (DAG) in modulating chronic inflammation and chronic diseases, the potential mechanisms of its involvement in TLRs-mediated inflammation are still unclear. Here, we show that sn-1,2-diacylglycerols modulate LPS/TLR4-mediated inflammation in vitro and in vivo. ELISA and western blotting experiments indicated that sn-1,2-diacylglycerols suppress LPS-induced responses, including IL-6 and TNF-α production, and COX-2 expression in mouse RAW264.7 macrophages and human endothelial cells, in a dose-dependent manner. Using LPS-induced murine model of systemic inflammation, we show that sn-1,2-diacylglycerols block the cytokine storm, the expression of inflammatory mediators, and LPS-induced septic lung damage and mortality. sn-1,2-diacylglycerols reduce systemic inflammation by inhibiting LPS-induced p38 MAPK- and PI3K/AKT-mediated NF-κB activation in macrophages. These results suggest that exogenous DAG probably acts by blocking p38 MAPK or PI3K/AKT signal transduction, thereby down-regulating NF-κB activation and NF-κB-mediated transcription of genes encoding cytokines and pro-inflammatory oxidative enzymes. Our findings demonstrate that exogenous sn-1,2-diacylglycerol protects mice from LPS-induced lethal endotoxemia by suppressing TLR4-driven inflammatory responses, suggesting that 1,2-diacylglycerols may be used as dietary health supplements for the prevention or therapy of systemic inflammatory diseases.

Rationale: Systemic inflammation has emerged as a key pathophysiological process that induces multiorgan injury and causes serious human diseases. Endothelium is critical in maintaining cellular and inflammatory homeostasis, controlling systemic inflammation, and progression of inflammatory diseases. We postulated that endothelium produces and releases endogenous soluble factors to modulate inflammatory responses and protect against systemic inflammation. Objective: To identify endothelial cell–released soluble factors that protect against endothelial barrier dysfunction and systemic inflammation. Methods and Results: We found that conditioned medium of endothelial cells inhibited cyclooxgenase-2 and interleukin-6 expression in macrophages stimulated with lipopolysaccharide. Analysis of conditioned medium extracts by liquid chromatography–mass spectrometry showed the presence of 5-methoxytryptophan (5-MTP), but not other related tryptophan metabolites. Furthermore, endothelial cell–derived 5-MTP suppressed lipopolysaccharide-induced inflammatory responses and signaling in macrophages and endotoxemic lung tissues. Lipopolysaccharide suppressed 5-MTP level in endothelial cell-conditioned medium and reduced serum 5-MTP level in the murine sepsis model. Intraperitoneal injection of 5-MTP restored serum 5-MTP accompanied by the inhibition of lipopolysaccharide-induced endothelial leakage and suppression of lipopolysaccharide- or cecal ligation and puncture–mediated proinflammatory mediators overexpression. 5-MTP administration rescued lungs from lipopolysaccharide-induced damages and prevented sepsis-related mortality. Importantly, compared with healthy subjects, serum 5-MTP level in septic patients was decreased by 65%, indicating an important clinical relevance. Conclusions: We conclude that 5-MTP belongs to a novel class of endothelium-derived protective molecules that defend against endothelial barrier dysfunction and excessive systemic inflammatory responses.

Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks in sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations. The validation results indicated that the data fusion approach reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high-accuracy surface modelling to fuse the ground sample plots with the satellite observations (HASM-S). The estimates produced with HASM-S were 26.1 and 28.4 % more accurate than the satellite-based approach and spatial interpolation of the sample plots respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-S method.

This study presents a computational framework to investigate the structural mechanism of glass forming ability (GFA) by carefully comparing two model systems of Zr-based binary metallic glasses (MGs) with distinct GFAs, Zr2Cu and Zr2Ni. Based on the Voronoi diagram of three-dimensional spherical atoms, the free volume, the cluster regularity, and the atomic packing efficiency in the atomic structure of Zr2Cu and Zr2Ni MGs are efficiently and accurately calculated as a function of temperature during quenching from melts to MGs. The glass transitions were found to occur with the fractional free volume reaching a seemingly universal value at ∼2%–3%. Although the glass states of both MGs show very similar linear temperature-dependent behavior, their supercooled liquid states behave quite differently, e.g., the structure of Zr2Cu changes much faster than that of Zr2Ni, and by extrapolating the temperature dependence of the free volume of liquids, the free-volume could quickly vanish in the Zr2Cu supercooled liquid at ∼210 K, while it remains even down to 0 K in Zr2Ni. In addition, Zr2Cu has higher atomic packing density and cluster regularity at low temperature region, also is more spatially homogeneous than Zr2Ni. These results reveal clear structure characteristics which are associated with the viscosity of the supercooled liquids and the Gibbs energy of glass states, therefore, the GFA and stability of MGs.

High accuracy surface modeling (HASM) has been proved to be a superior method for surface simulation compared to classical interpolation methods. However, the fact that HASM is time consuming combined with its dependence on its driving field restricts its application in large area problems. This research develops a modified HASM which can get rid of the driving field in the surface simulation, and the parallel version of the modified HASM is also proposed with the purpose of improving its computational efficiency. Light detection and ranging (LIDAR) data are used as an optimum constraint to construct digital elevation model (DEM). Tests show that the modified HASM can perform surface simulation successfully without the driving field. And it also shows that the simulation accuracy of the modified HASM is almost the same as the old HASM and the classical interpolation methods when the sampling rate is larger than 0.5 %, while the modified HASM shows significantly increased simulation accuracy as the sampling rate decreases. This characteristic indicates that the modified HASM no longer relies on the driving field in the surface simulation. And it also improves the simulation accuracy compared to the old HASM and the classical interpolation methods. Tests of parallel efficiency show that the master–slave mode used in the parallel algorithm obtains a satisfactory result, indicating that the HASM can be applied to surface simulation of large area problems. And it also shows that the modified HASM would have great potential where applied in high-resolution DEM and digital surface model (DSM) construction from LIDAR data.

Begonia grandis Dry. (Begoniaceae), previously recognized as endemic to continental China, was recently discovered from southern Taiwan. Close morphological observations and molecular phylogenetic analysis elucidated that the species in Taiwan belongs to subspecies grandis. Begonia grandis has a long history in cultivation especially in China and Japan but not in Taiwan. The collection locality in Taiwan had no trace of human activity. Therefore, B. grandis is considered to be native to Taiwan. The new finding in Taiwan marks the southernmost distribution record of the species. Unfortunately, the discovered population was destroyed by a landslide due to a typhoon in 2009. Further field survey in neighboring areas is needed to elucidate the current status of B. grandis in Taiwan.

The height–diameter relationship model is crucial in the estimation of forest stand volume, biomass and carbon storage, etc. To improve prediction accuracy, the classified factors method for height–diameter relationship modeling was developed based on the classified height method. The data set contained 959 tree samples obtained from 28 plots measured by topographic factors (aspect, slope position and altitude). The Chapman–Richards equation was used to build models. Classification methods have improved fitting performance and prediction accuracy compared to the classical method. The classified height method has the best fitting performance because it has the highest determination coefficient (R2 = 0.927) and the lowest root mean square error (RMSE = 1.548), whereas the classified factors method has the highest prediction accuracy because it has the lowest mean absolute error (MAE = 1.137) and mean relative error (MRE = 0.109).

Development of novel approaches for biofouling mitigation is of crucial importance for membrane-based technologies. d-amino acids (d-AAs) have been proposed as a potential strategy to mitigate biofouling. However, the effect of bacterial cell-wall properties and d-AAs type on biofouling mitigation remains unclear. This study assesses the effect of d-AAs type on membrane biofouling control, towards Gram positive (G+) and Gram negative (G-) bacteria. Three kinds of d-AAs were found to inhibit both G+ and G- bacterial attachment in short-term attachment and dead-end filtration experiments. The existence of d-AAs reduces extracellular polysaccharides and proteins on the membrane, which may decrease membrane biofouling. Cross-flow filtration tests further indicated that d-AAs could effectively reduce membrane biofouling. The permeate flux recovery post chemical cleaning, improved for both P. aeruginosa and B. subtilis treated with d-AAs. The results obtained from this study enable better understanding of the role of d-AAs species on bacterial adhesion and biofilm formation. This may provide a new way to regulate biofilm formation by manipulating the species of d-AAs membrane systems.

Bacterial biofilms are structured communities of cells enclosed in a self-produced hydrated polymeric matrix that can adhere to inert or living surfaces. D-Amino acids were previously identified as self-produced compounds that mediate biofilm disassembly by causing the release of the protein component of the polymeric matrix. However, whether exogenous D-amino acids could inhibit initial bacterial adhesion is still unknown. Here, the effect of the exogenous amino acid D-tyrosine on initial bacterial adhesion was determined by combined use of chemical analysis, force spectroscopic measurement, and theoretical predictions. The surface thermodynamic theory demonstrated that the total interaction energy increased with more D-tyrosine, and the contribution of Lewis acid-base interactions relative to the change in the total interaction energy was much greater than the overall nonspecific interactions. Finally, atomic force microscopy analysis implied that the hydrogen bond numbers and adhesion forces decreased with the increase in D-tyrosine concentrations. D-Tyrosine contributed to the repulsive nature of the cell and ultimately led to the inhibition of bacterial adhesion. This study provides a new way to regulate biofilm formation by manipulating the contents of D-amino acids in natural or engineered systems.

The electronic structures, chemical bonding, elastic and optical properties of the novel hP24 phase WB3 were investigated by using density-functional theory (DFT) within generalized gradient approximation (GGA). The calculated energy band structures show that the hP24 phase WB3 is metallic material. The density of state (DOS) and the partial density of state (PDOS) calculations show that the DOS near the Fermi level is mainly from the W 5d and B 2p states. Population analysis suggests that the chemical bonding in hP24-WB3 has predominantly covalent characteristics with mixed covalent-ionic characteristics. Basic physical properties, such as lattice constant, bulk modulus, shear modulus and elastic constants C ij were calculated. The elastic modulus E and Poisson ratio ν were also predicted. The results show that hP24-WB3 phase is mechanically stable and behaves in a brittle manner. Detailed analysis of all optical functions reveals that WB3 is a better dielectric material, and reflectivity spectra show that WB3 can be promised as good coating material in the energy regions of 8.5–11.4 eV and 14.5–15.5 eV.

Humanity has an urgent need to develop more degradable materials for solving environmental pollution. In this study, through host–guest interactions between fatty acids-modified β-cyclodextrin (Em-βCD) and polyethylenimine (PEI) oligomer-grafted ferrocene (PEI-Fc), we designed and prepared a supramolecular polymer (PEI-Fc/Em-βCD complex), which showed polymeric properties and was able to be used as a cushioning material due to its good compressibility. Compared with conventional polymers, a remarkable advantage of the PEI-Fc/Em-βCD complex is that it can be dismantled into small molecules and rebuilt easily by controlling the dissociation or reformation of βCD-Fc inclusion complexes. Furthermore, the material also exhibited good self-healing properties.

The electronic structures, chemical bonding and elastic properties of the Co 2 P-type structure phase ultra-incompressible Re 2 P (orthorhombic phase) were investigated by density-functional theory (DFT) within generalized gradient approximation (GGA). The calculated energy band structures show that the orthorhombic structure phase Re 2 P is metallic material. The density of state (DOS) and the partial density of state (PDOS) calculations show that the DOS near the Fermi level is mainly from the Re-5d state. Population analysis suggests that the chemical bonding in Re 2 P has predominantly covalent character with mixed covalent-ionic character. Basic physical properties, such as lattice constant, bulk modulus, shear modulus, and elastic constants C ij , were calculated. The elastic modulus and Poisson ratio were also predicted. The results show that the Co 2 P-type structure phase Re 2 P is mechanically stable and behaves in a brittle manner.

In the area of finance, the stochastic volatility (SV) model is a useful tool for modelling stock market returns. However, there is evidence that asymmetric behaviour of stock returns exists. A threshold SV (THSV) model is provided to capture this behaviour. In this study, we introduce a robust model created through empirical Bayesian analysis to deal with the uncertainty between the SV and THSV models. A Markov chain Monte Carlo algorithm is applied to empirically select the hyperparameters of the prior distribution. Furthermore, the value at risk from the resulting predictive distribution is also given. Simulation studies show that the proposed empirical Bayes model not only clarifies the acceptability of prediction but also reduces the risk of model uncertainty.

Myopia is becoming a significant public health problem, affecting more and more people. Studies indicate that there are two main factors, hereditary and environmental, suspected to have strong impact on myopia. Motivated by the increase in the number of people affected by this problem, this paper focuses primarily on the utilization of mathematical methods to gain further insight into their relationship with myopia. Accordingly, utilizing multidimensional longitudinal myopia data with correlation between both eyes, we develop a Bayesian structural equation model including random effects. With the aid of the MCMC method, it is capable of expressing the correlation between repeated measurements as well as the two-eye correlation and can be used to explore the relational structure among the variables in the model. We consider four observed factors, including intraocular pressure, anterior chamber depth, lens thickness, and axial length. The results indicate that the genetic effect has much greater influence on myopia than the environmental effects. Copyright © 2011 John Wiley & Sons, Ltd.

Structural equation models (SEM) have been extensively used in behavioral, social, and psychological research to model relations between the latent variables and the observations. Most software packages for the fitting of SEM rely on frequentist methods. Traditional models and software are not appropriate for analysis of the dependent observations such as time-series data. In this study, a structural equation model with a time series feature is introduced. A Bayesian approach is used to solve the model with the aid of the Markov chain Monte Carlo method. Bayesian inferences as well as prediction with the proposed time series structural equation model can also reveal certain unobserved relationships among the observations. The approach is successfully employed using real Asian, American and European stock return data.

In this work, the deformation of Zr2Cu metallic glass (MG) under uniaxial tensile stress was investigated at the atomic level using a series of synchrotron radiation techniques combined with molecular dynamics simulation. A new approach to the quantitative detection of free volumes in MGs was designed and it was found that free volumes increase in the elastic stage, slowly expand in the yield stage, and finally reach saturation in the plastic stage. In addition, in different regions of the MG model, free volumes exhibited inhomogeneity under stress, in terms of size, density, and distribution. In particular, the expansion of free volumes in the center region was much more rapid than those in the other regions. It is interesting that the density of free volumes in the center region abnormally decreased with strain. It was revealed that the atomic-level stress between different regions may contribute to the inhomogeneity of free volumes under stress. In addition, the inhomogeneous change of free volumes during the deformation was confirmed by the evolution of local atomic shear strains in different regions. The present work provides in-depth insight into the deformation mechanisms of MGs.

The endothelial junction is tightly controlled to restrict the passage of blood cells and solutes. Disruption of endothelial barrier function by bacterial endotoxins, cytokines or growth factors results in inflammation and vascular damage leading to vascular diseases. We have identified 5-methoxytryptophan (5-MTP) as an anti-inflammatory factor by metabolomic analysis of conditioned medium of human fibroblasts. Here we postulated that endothelial cells release 5-MTP to protect the barrier function. Conditioned medium of human umbilical vein endothelial cells (HUVECs) prevented endothelial hyperpermeability and VE-cadherin downregulation induced by VEGF, LPS and cytokines. We analyzed the metabolomic profile of HUVEC conditioned medium and detected 5-MTP but not melatonin, serotonin or their catabolites, which was confirmed by enzyme-linked immunosorbent assay. Addition of synthetic pure 5-MTP preserved VE-cadherin and maintained barrier function despite challenge with pro-inflammatory mediators. Tryptophan hydroxylase-1, an enzyme required for 5-MTP biosynthesis, was downregulated in HUVECs by pro-inflammatory mediators and it was accompanied by reduction of 5-MTP. 5-MTP protected VE-cadherin and prevented endothelial hyperpermeability by blocking p38 MAPK activation. A chemical inhibitor of p38 MAPK, SB202190, exhibited a similar protective effect as 5-MTP. To determine whether 5-MTP prevents vascular hyperpermeability in vivo, we evaluated the effect of 5-MTP administration on LPS-induced murine microvascular permeability with Evans blue. 5-MTP significantly prevented Evans blue dye leakage. Our findings indicate that 5-MTP is a new class of endothelium-derived molecules which protects endothelial barrier function by blocking p38 MAPK.

Using the T-H solid solution made by titanium absorbed hydrogen as the cathode, the Ti-H plasma produced by the pulsed vacuum are ion source was nonequilibrium: it contained both the component of titanium and hydrogen; there existed gradient in the radiaL, the horizontal and the time. As a result, it could not be described by a single temperature. The present paper assumed that the subsystem consisting of electrons and the subsystem consisting of other heavy particles reached equilibrium respectively, meaning that the Ti-H plasma was described by the two temperatures as electron temperature and heavy ion temperature, it was non-equilibrium two-temperature plasma Using Culdberg-Waage dissociation equation to describe the molecular dissociation process in the system, using Saha ionization equation to describe the atomic ionization process, combining plasma's charge quasi-neutral condition and introducing atomic emission spectroscopy as a plasma diagnostic method which would not interfere the plasma at the same time; the temperature and the particle number density of the Ti-H plasma were diagnosed. Using MATLAB as a tool, both the titanium atoms and monovalent titanium ions' ionization were considered, and the calculated results showed that with the electtron density determined by the Stark broadening of spectral lines in advance, except the heavy particle temperature and the hydrogen number density, the Ti-H plasma's parameters could be diagnosed fairly accurately; the accuracy of the electron density values had a great effect on the calculation results; if the heavy particle temperature could be determined in advance, the temperature and the particle number density of the Ti-H plasma could be accurately analyzed quantitatively.

In order to study the discharge process of vacuum arc ion source, make a detail description of the discharge plasma, and lay the foundation for further research on ion source, atomic emission spectrometry was used to diagnose the parameters of plasma produced by vaccum arc ion source. In the present paper, two kinds of analysis method for the emission spectra data collected by a spectrometer were developed. Those were based in the stark broadening of spectral lines and Saba-Boltzmann equation. Using those two methods, the electron temperature, electron number density and the ion temperature of the plasma can be determined. The emission spectroscopy data used in this paper was collected from the plasma produced by a vacuum are ion source whose cathode was made by Ti material (which adsorbed hydrogen during storage procedure). Both of the two methods were used to diagnose the plasma parameters and judge the thermal motion state of the plasma. Otherwise, the validity of the diagnostic results by the two methods were analyzed and compared. In addition, the affection from laboratory background radiation during the spectral acquisition process was discussed.

To analyze the real-time effects of electroacupuncture (EA) stimulation by means of multiport network theory and measurement of the electric signals transfer coefficient, so as to explore a way for determining the running course of acupuncture meridian and for characterizing its physiological activities in the living body.The body was modeled as a complex inhomogeneous 3-dimensions multi-port network, and the meridians were assumed to be "the most smoothly channels for signal transmission". Experiments were performed in 12 beheaded toads whose forelimbs and hindlimbs were divided into proportional coordinates. A concentric electrode with a conical tip was inserted into the toad leg for electrical stimulation of the local muscle, and another electrode alike was inserted into different spots of the limbs to detect the spreading signals in a 3-dimensional scanning mode. Following detecting the response electric voltage values of various spots and calculating their transfer coefficients, the spots which acquired a maximum signal value were considered to be the "acupoints". The imaginary connective lines passing the "acupoints" were regarded as the running courses of acupuncture meridians.A total of twelve 3-dimensional curves were detected based on the connected lines of electric signal transfer function extremum spots 2 mm beneath the skin of the ipsilateral fore- and hind-limbs of 12 spinal toads.The present study initially validates the feasibility of electric signal transfer coefficient measurement for displaying the running course of acupuncture meridian in the toad fore- and hindlimbs.

The sludge floc stability is essential for the solid/liquid separation in biological wastewater treatment. In this study, the effect of an exogenous d-tyrosine on the shear stability and surface characteristics of activated sludge flocs was investigated. Sludge flocs were found to be less stable in the addition of d-tyrosine. d-Tyrosine inhibited the production of extracellular polymeric substances (EPS) especially for the proteins. A high correlation coefficient was observed between the composition of EPS fraction and d-tyrosine content. In addition, the hydrophobicity of sludge flocs was reduced and the zeta potential was more negative with the content of d-tyrosine increased. A linear relationship between the extracellular polymeric substances and surface characteristics for sludge flocs indicated that the inhibited EPS production may be responsible for the instability of sludge upon the addition of d-tyrosine.

A novel pH-switchable macroscopic assembly is reported using alginate-based hydrogels functionalized with host (alpha-cyclodextrin, alpha CD) and guest (diethylenetriamine, DETA) moieties. Since the interaction of alpha CD and DETA is pH sensitive, the host hydrogel and guest hydrogel could adhere together when the pH is 11.5 and separate when the pH is 7.0. Furthermore, this pH-controlled adhesion and dissociation shows a good reversibility. The host and guest polymers have good biocompatibility; therefore, this pH-sensitive macroscopic assembly shows great potential in biotechnological and biomedical applications.

A novel redox-induced shape-memory polymer (SMP) is prepared by crosslinking β-cyclodextrin modified chitosan (β-CD-CS) and ferrocene modified branched ethylene imine polymer (Fc-PEI). The resulting β-CD-CS/Fc-PEI contains two crosslinks: reversible redox-sensitive β-CD-Fc inclusion complexes serving as reversible phases, and covalent crosslinks serving as fixing phases. It is shown that this material can be processed into temporary shapes as needed in the reduced state and recovers its initial shape after oxidation. The recovery ratio and the fixity ratio are both above 70%. Furthermore, after entrapping glucose oxidase (GOD) in the system, the material shows a shape memory effect in response to glucose. The recovery ratio and the fixity ratio are also above 70%.

Photoreversible micelles were achieved by a combination of commercially available components sodium alginate (Alg), tetradecyltrimethylammonium bromide (TTAB), α-cyclodextrin (α-CD), and 4-(phenylazo)benzoic acid (PBA). Under visible light irradiation, α-CD interacted more favorably with PBA than with alkyl chains of TTAB. Therefore, polymer–surfactant micelles were formed by the self-assembly of Alg and TTAB through electrostatic attraction. After UV irradiation, micelles were disrupted because PBA in the cis form lost its ability to complex with α-CD, and then the latter was interacted with TTAB to prevent the association of alkyl chains of TTAB. On alternating irradiation of this quaternary system with UV and visible light, this reversible micellization process can be recycled many times.